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Course Description
This course introduces fundamentals concepts related to artificial intelligence (AI), and the services in Microsoft Azure that can be used to create AI solutions. The course is not designed to teach students to become professional data scientists or software developers, but rather to build awareness of common AI workloads and the ability to identify Azure services to support them.
Who Should Attend?
The Azure AI Fundamentals course is designed for anyone interested in learning about the types of solution artificial intelligence (AI) makes possible, and the services on Microsoft Azure that you can use to create them. You don’t need to have any experience of using Microsoft Azure before taking this course, but a basic level of familiarity with computer technology and the Internet is assumed. Some of the concepts covered in the course require a basic understanding of mathematics, such as the ability to interpret charts. The course includes hands-on activities that involve working with data and running code, so a knowledge of fundamental programming principles will be helpful.
About this course
Course Outline
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Describe Artificial Intelligence workloads and considerations (20–25%)
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Describe fundamental principles of machine learning on Azure (25–30%)
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Describe features of computer vision workloads on Azure (15–20%)
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Describe features of Natural Language Processing (NLP) workloads on Azure (25–30%)
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Identify features of anomaly detection workloads
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Identify computer vision workloads
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Identify natural language processing workloads
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Identify knowledge mining workloads
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Describe considerations for fairness in an AI solution
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Describe considerations for reliability and safety in an AI solution
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Describe considerations for privacy and security in an AI solution
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Describe considerations for inclusiveness in an AI solution
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Describe considerations for transparency in an AI solution
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Describe considerations for accountability in an AI solution
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Identify regression machine learning scenarios
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Identify classification machine learning scenarios
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Identify clustering machine learning scenarios
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Identify features and labels in a dataset for machine learning
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Describe how training and validation datasets are used in machine learning
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Automated machine learning
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Azure Machine Learning designer
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Identify features of image classification solutions
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Identify features of object detection solutions
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Identify features of optical character recognition solutions
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Identify features of facial detection and facial analysis solutions
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Identify capabilities of the Computer Vision service
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Identify capabilities of the Custom Vision service
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Identify capabilities of the Face service
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Identify capabilities of the Form Recognizer service
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Identify features and uses for key phrase extraction
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Identify features and uses for entity recognition
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Identify features and uses for sentiment analysis
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Identify features and uses for language modeling
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Identify features and uses for speech recognition and synthesis
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Identify features and uses for translation
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Identify capabilities of the Language service
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Identify capabilities of the Speech service
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Identify capabilities of the Translator service
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Identify features and uses for bots
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Identify capabilities of the Power Virtual Agents and Azure Bot service
Prerequisites
Prerequisite certification is not required before taking this course. Successful Azure AI Fundamental students start with some basic awareness of computing and internet concepts, and an interest in using Azure AI services.
Specifically:
- Experience using computers and the internet.
- Interest in use cases for AI applications and machine learning models.
- A willingness to learn through hands-on exploration.
Where
This will be a virtual event hosted on Microsoft Teams. In the Microsoft Teams platform and sessions, your name, email address, or title may be viewable by other participants. By joining this event, you agree to this experience.